A study on the closed-loop performance in extrapolated regions of operations of nonlinear systems using parallel OBF-NN models

Zabiri, H. and Marappagounder, R. and Lemma, T.D. (2016) A study on the closed-loop performance in extrapolated regions of operations of nonlinear systems using parallel OBF-NN models. Journal of Chemical Engineering of Japan, 49 (2). pp. 176-185. ISSN 00219592

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Abstract

Empirical models tend to suffer from unreliable extrapolation behavior, and this presents an issue when they are applied in model-based controller strategies such as nonlinear model predictive control (NMPC). This paper presents the development and implementation of the parallel OBF-NN model in the NMPC framework. The aim is to evaluate the applicability and the potential extrapolation benefits of the model in a closed-loop environment. For this purpose, closed-loop performance comparison is analyzed between the parallel OBF-NN and the conventional neural networks (NN) models. Results on two nonlinear case studies show that the NMPC based on the parallel OBF-NN model notably improved the closed-loop performance in the extrapolated regions of operation when compared to NMPC based on the conventional NN model without the need for re-training or any adaptive scheme. © 2016 The Society of Chemical Engineers, Japan.

Item Type: Article
Additional Information: cited By 0
Uncontrolled Keywords: Extrapolation; Neural networks; Nonlinear systems; Predictive control systems, Adaptive scheme; Closed loops; Closed-loop performance; Empirical model; Model-based controller; Neural network (nn); Nonlinear model predictive control; Orthonormal basis, Model predictive control
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:18
Last Modified: 09 Nov 2023 16:18
URI: https://khub.utp.edu.my/scholars/id/eprint/7171

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